A novel sequence and context based method for promoter recognition

Abstract

Identification of promoters in DNA sequence using computational techniques is a significant research area because of its direct association in transcription regulation. A wide range of algorithms are available for promoter prediction. Most of them are polymerase dependent and cannot handle eukaryotes and prokaryotes alike. This study proposes a polymerase independent algorithm, which can predict whether a given DNA fragment is a promoter or not, based on the sequence features and statistical elements. This algorithm considers all possible pentamers formed from the nucleotides A, C, G, and T along with CpG islands, TATA box, initiator elements, and downstream promoter elements. The highlight of the algorithm is that it is not polymerase specific and can predict for both eukaryotes and prokaryotes in the same computational manner even though the underlying biological mechanisms of promoter recognition differ greatly. The proposed Method, Promoter Prediction System - PPS-CBM achieved a sensitivity, specificity, and accuracy percentages of 75.08, 83.58 and 79.33 on E. coli data set and 86.67, 88.41 and 87.58 on human data set. We have developed a tool based on PPS-CBM, the proposed algorithm, with which multiple sequences of varying lengths can be tested simultaneously and the result is reported in a comprehensive tabular format. The tool also reports the strength of the prediction.AvailabilityThe tool and source code of PPS-CBM is available at http://keralabs.org

Molecular dynamics simulation-based trinucleotide and tetranucleotide level structural and energy characterization of the functional units of genomic DNA

“…These tools offer good accuracy but are highly genome specific. [10][11][12][13][14][15][16] Despite the many insights gained over the years from such investigations, the creation of a promoter prediction tool capable of high performance across diverse organisms is still a long way off. 6 Eukaryotes are complex organisms that have a membranebound nucleus and cell organelles.…”

“…8), the occurrences of TAA and TGA were higher at the À1, 0, and +1 positions than any other trimer, while GTA and GTG were higher at the À2, À1, and 0 positions of the exon-end sites, confirming the conventional wisdom of the occurrence of these nucleotides at the said sites. [7][8][9][10][11][12][13][14][15][16][17] These motifs undoubtedly have the potential to aid in the prediction of exon-end sites. However, taking into consideration the total size (328 364) of the data, the frequency of occurrence is not high, and further, there is no consistent motif to rely on.…”

“…At the exon start site, there was again a higher occurrence of the AGGTA pentanucleotide for the motif À2, À1, 0, 1, 2, facilitating the prediction of the concerned sites and confirming the conventional belief of the occurrence of the A-G nucleotide at the 3 0 end of the intron. [7][8][9][10][11][12][13][14][15][16][17] To gain deeper insight into the nucleotide sequence pattern frequency at the exon-intron boundaries, an undecamer position motif extending from À5 to +5, with the exon start/end site positioned at 0, was considered (Fig. 10).…”